1. Field of the Invention
The present invention relates to a method and a system for optimizing a plurality of structural parameters using a computer, and further relates to a method for manufacturing an industrial product with optimized manufacturing conditions, processing through a sequence of manufacturing processes.
2. Description of the Related Art
Recently, optimization design for a semiconductor device by simulating manufacturing processes and electrical characteristics of the semiconductor device using technology computer aided design (TCAD) has come into frequent use.
In order to achieve excellent functional characteristics of a minute semiconductor device, such as a metal-oxide semiconductor field effect transistor (MOSFET), so as to optimize a structure of the semiconductor device, various experiments and simulations, based on a response surface method or an orthogonal array experiment, are executed. Because it is possible to examine optimization without actually performing a trial manufacture, it is particularly suitable to use simulation in such an optimization method.
For example, a system for attaining a desired calculation result by automatically changing input data of the simulation based on a previously specified condition using an optimal value search method such as a quasi Newton method, or a design of experiment (DOE) method using an orthogonal array, has been proposed (refer to Japanese Patent Laid Open No. 2002-259463).
Although input data used in a simulation of the semiconductor device normally includes several hundred to several thousand of variable manufacturing parameters, it is very rare to change all values of the manufacturing parameters in a series of simulations for optimizing a structure of the semiconductor device. Only the manufacturing parameters assumed to have a large or strong influence on target characteristics may be changed. This is because, dimensions of an optimum solution search domain excessively increase when dealing with significantly numerous parameters, and thus an enormous number of operations will be required with an optimal value search method such as the quasi Newton method, or the DOE method using an orthogonal array. However, in the optimal solution search methods or the DOE method, in an absence of interactions and singularities assuming only a main effect affecting a strong effect on each parameter, in theory it is possible to greatly reduce the number of operations.
However, when designing parameters to optimize quality performance of a MOSFET, such as a driving current (Ion) and a standby leak current (hereinafter called “off leak current”, Ioff), which greatly vary in response to a threshold voltage Vth, by the DOE method using an orthogonal array, average values and variances of the characteristics are estimated by an average value calculation of the orthogonal array.
Because there is a trade-off between the Ion and Ioff characteristics due to interaction, errors in estimation of the characteristics are increased. Therefore, it is impossible to estimate the optimum solution from the main effect, when dealing with numerous parameters.
In optimization of a complicated structure, such as a MOSFET, it is understood that the structure to be optimized may include many characteristics and many manufacturing parameters. A plurality of characteristics may depend on common manufacturing parameters. Additionally, a trade-off relation in which, when attaining a specification of a specific target characteristic by changing values of manufacturing parameters, other target characteristic may not be attained. Such a situation may easily occur in an optimization examination. Thus, in an optimization design of a structure having target characteristics which are in a trade-off relation, it is necessary to search for a manufacturing parameter which will not commonly affect target characteristics, or a manufacturing parameter having no trade-off effect on target characteristics. Therefore, if level values of many manufacturing parameters are not inevitably dealt with, it is impossible to eliminate the trade-off relation between the target characteristics.
By advances in the operation performance of an engineering work station (EWS), simulation processing, such as changes to input data, activation of a simulator, and arrangement of calculation results, which have been handled by human resources, is automated to improve the efficiency of optimization design of a semiconductor device and the like. It has become easier to run the simulation by allocating input values to a plurality of manufacturing parameters based on an orthogonal array. By conducting a total optimization design in which a plurality of target characteristics can be simultaneously satisfied by dealing with many parameters in a simulation, the efficiency of optimization design will be remarkably increased. However, the possibility of the presence of interactions and singularities makes it difficult to achieve optimization design using multiple parameters.